A Management Algorithm for High-Grade Acute Cholecystitis in High-Risk Patients - Morley, Timothy J.; Fridling, Jeremy; Brewer, Jennifer M.; Gross, Ronald; Montgomery, Stephanie; Miller, Corrine; Posillico, Sarah; Jeremitsky, Elan; Jayaraman, Vijay; Roberts, Kurt E.; Hill, Thomas Russell; Moutinho, Manuel; et al. (Journal of the Society of Laparoendoscopic Surgeons, 2025)
Acute cholecystitis (AC) is among the most frequently encountered surgical problems. Current management typically includes laparoscopic cholecystectomy (LC). Suboptimal outcomes of LC can include bile duct injury, open conversion (OC), and/or subtotal cholecystectomy (SC). Percutaneous cholecystostomy tube (PCT) drainage with interval cholecystectomy has emerged as an alternative in high-risk patients but outcomes vary widely. We describe an evidence-based algorithm for managing AC in high-risk patients via PCT followed by minimally invasive cholecystectomy (MIS-C). We hypothesized that our algorithm would prove safe, effective, and decrease OC and SC rates. Retrospective chart review of patients undergoing PCT and MIS-C according to our algorithm from January 2020 to June 2023. The primary outcome was OC or SC. Secondary outcomes included bile leak, bile duct injury, and perioperative complications. Demographic, clinical, and operative data were collected. Statistical analysis was performed using Minitab Software. Twenty-nine patients met criteria and were treated according to our algorithm during the study period. One patient (3.4%) required conversion to SC. Other complications included 3 postoperative bile leaks (10.4%). There were no bile duct injuries and no deaths. None were lost to follow up. When stratified by LC or robotic-assisted cholecystectomy (RC), complications occurred more frequently in the LC group, including the lone conversion to SC. Our management protocol of high-grade AC in high-risk patients appears safe, feasible, and may reduce adverse events. Additionally, our data suggest a potential benefit of RC in this setting which may be an underutilized tool in acute care surgery. Prospective data are needed to validate and further refine this algorithm.